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相关概念视频

Difference Equation Solution using z-Transform01:24

Difference Equation Solution using z-Transform

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The z-transform is a powerful tool for analyzing practical discrete-time systems, often represented by linear difference equations. Solving a higher-order difference equation requires knowledge of the input signal and the initial conditions up to one term less than the order of the equation.
The z-transform facilitates handling delayed signals by shifting the signal in the z-domain, which corresponds to delaying the signal in the time domain, and advancing signals by similarly shifting in the...
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Phase Contrast and Differential Interference Contrast Microscopy01:26

Phase Contrast and Differential Interference Contrast Microscopy

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Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...
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Time and frequency -Domain Interpretation of Phase-lead Control01:24

Time and frequency -Domain Interpretation of Phase-lead Control

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Phase-lead controllers are commonly used in various control systems to enhance response speed and stability. Adjusting the brightness on a television screen offers a practical example of phase-lead control. When contrast is enhanced, a phase-lead controller is employed. Mathematically, phase-lead control is identified when the first parameter is smaller than the second.
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...
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Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

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Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
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Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

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Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
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相关实验视频

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Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization
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通过基于学习的算法进行噪声强大的泽尼克相位检索,仅使用两步相位转移测量.

Hansol Kim, Youngmo Jeong, Kyoungjae Lee

    Optics express
    |September 15, 2023
    PubMed
    概括

    这项研究引入了一种新的深度学习方法,用于分析只使用两个相位移测量的光学偏差. 与现有的四步技术相比,新的两步方法显示出更高的噪声稳定性和效率.

    科学领域:

    • 光学工程是指光学工程.
    • 计算光学是指计算机光学.
    • 机器学习 机器学习

    背景情况:

    • 偏差分析对于光学系统的性能至关重要.
    • 现有的方法通常需要多次测量,并且对噪声敏感.
    • 开发高效和强大的偏差分析技术是一个持续的挑战.

    研究的目的:

    • 开发一种基于深度学习的噪声强大的偏差分析方法,使用两步相位移数据.
    • 为训练深度神经网络创建一个现实的合成数据集.
    • 在准确性和速度上超越现有的四步代方法.

    主要方法:

    • 提出了一种使用泽尼克系数统计分布的现实的偏差模式生成方法.
    • 综合了大量的数据集 (200000个误差) 用于培训.
    • 在合成数据集上训练深度神经网络 (GoogLeNet,ResNet101).
    • 评估了两步方法与四步方法 (衍生配件,TIE,坚固的TIE) 相比.

    主要成果:

    • 两步深度学习方法在噪声稳定性,RMSE和数值生成异常的推理时间方面明显优于四步方法.
    • 实验验证显示,RMSE与现实世界偏差的四步方法相比较.

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  • 定性分析显示,与现有方法相比,边缘模式和相分布的重建优越.
  • 结论:

    • 拟议的两步深度学习方法为全面的偏差分析提供了实用和高效的方法.
    • 该方法表现出极好的噪声稳定性和计算速度.
    • 扩展到更高阶异常和进一步性能改进的潜力.